With the emergence of the Web of Data, there is a need of tools for searching and exploring the growing amount of semantic data. Unfortunately, such tools are scarce and typically require knowledge of SPARQL/RDF. We propose here PepeSearch, a portable tool for searching semantic datasets devised for mainstream users. PepeSearch offers a multi-class search form automatically constructed from a SPARQL endpoint. We have tested PepeSearch with 15 participants searching a Linked Open Data version of the Norwegian Register of Business Enterprises for non-trivial challenges. Retrieval performance was encouragingly high and usability ratings were also very positive, thus suggesting that PepeSearch is effective for searching semantic datasets by mainstream users. We also assessed its portability by configuring PepeSearch to query other SPARQL endpoints.

In this paper we tackle the problem of answering SPARQL queries over virtually integrated databases. We assume that the entity resolution problem has already been solved and explicit information is available about which records in the different databases refer to the same real world entity. Surprisingly, to the best of our knowledge, there has been no attempt to extend the standard Ontology-Based Data Access (OBDA) setting to take into account these DB links for SPARQL query-answering and consistency checking. This is partly because the OWL built-in owl:sameAs property, the most natural representation of links between data sets, is not included in OWL 2 QL, the de facto ontology language for OBDA. We formally treat several fundamental questions in this context: how links over database identifiers can be represented in terms of owl:sameAs statements, how to recover rewritability of SPARQL into SQL (lost because of owl:sameAs statements), and how to check consistency. Moreover, we investigate how our solution can be made to scale up to large enterprise datasets. We have implemented the approach, and carried out an extensive set of experiments showing its scalability.

This paper elaborates on ontology-based end-user visual query formulation, particularly for users who otherwise cannot/do not desire to use formal textual query languages to retrieve data due to the lack of technical knowledge and skills. Then, it provides a set of quality attributes and features, primarily elicited via a series of industrial end-user workshops and user studies carried out in the course of an industrial EU project, to guide the design and development of successor visual query systems.

Data access in an enterprise setting is a determining factor for value creation processes, such as sense-making, decision-making, and intelligence analysis. Particularly, in an enterprise setting, intuitive data access tools that directly engage domain experts with data could substantially increase competitiveness and profitability. In this respect, the use of ontologies as a natural communication medium between end users and computers has emerged as a prominent approach. To this end, this article introduces a novel ontology-based visual query system, named OptiqueVQS, for end users. OptiqueVQS is built on a powerful and scalable data access platform and has a user-centric design supported by a widget-based flexible and extensible architecture allowing multiple coordinated representation and interaction paradigms to be employed. The results of a usability experiment performed with non-expert users suggest that OptiqueVQS provides a decent level of expressivity and high usability and hence is quite promising.

Querying is an essential instrument for meeting ad hoc information needs; however, current approaches for querying semantic data sources mostly target technologically versed users. Hence, there is a need for methods that make it possible for users with limited technological skills to express relatively complex ad hoc information needs in an easy and intuitive way. Visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. In this paper, we present an ontology-based visual query system, OptiqueVQS, and report user experiments in two industrial settings.

The variable splitting method for free-variable tableau calculi provides an admissibility condition under which the same free variables can be assigned values independently on different branches. While this has a large potential for automated proof search, a direct implementation of this condition is impractical. We adapt the incremental closure framework for free variables to variable splitting tableaux by recasting the admissibility condition for closing substitutions into a constraint satisfaction problem. The resulting mechanism allows to check the existence of an admissible closing substitution incrementally during the construction of a proof. We specify a rule-based algorithm for testing satisfiability of constraints that accounts for split variables, and present experimental results based on a prototype variable splitting theorem prover implementation measuring the computational overhead of the variable splitting framework.

Software is vital for modern society. It is used in many safety- or security-critical applications, where a high degree of correctness is desirable. Over the last years, technologies for the formal specification and verification of software—using logic-based specification languages and automated deduction—have matured and can be expected to complement and partly replace traditional software engineering methods in the future. Program verification is an increasingly important application area for automated deduction. The field has outgrown the area of academic case studies, and industry is showing serious interest. This article describes the aspects of automated deduction that are important for program verification in practise, and it gives an overview of the reasoning mechanisms, the methodology, and the architecture of modern program verification systems.

We report work carried out within the CODIO project on COllaborative Decision support for Integrated Operations. As one part of this project, we have designed a system to provide assistance in operational decisions based on real-time sensor readings in a typical scenario: while drilling close to the transition to a high-pressure formation, a gas influx is observed. The drilling team needs to decide whether to circulate, increase the mud weight, plug back, set a casing, etc. After a brief description of the technology we used to model decision problems (Bayesian Networks, Influence Diagrams), we describe our case study and go on to apply the method of decision analysis to it. We discuss how the resulting influence diagram was tested using a simulation, and discuss challenges in applying the technology, as well as lessons learnt underway. We also give a list of desiderata to establish better decision making practices in the petroleum industry.

We define a probabilistic propositional logic for making a finite, ordered sequence of decisions under uncertainty by extending an existing probabilistic propositional logic with expectation and utility-independence formulae. The language has a relatively simple model semantics, and it allows a similarly compact representation of decision problems as influence diagrams. We present a calculus and show that it is complete at least for the type of reasoning possible with influence diagrams.